A new approach to global minimization

Stanton, Aaron; Bleil, R.; Kais, Sabre

doi:10.1002/(sici)1096-987x(199703)18:4<594::aid-jcc12>3.0.co;2-g

Cited by 15 publications

(10 citation statements)

References 15 publications

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“…The results and efficiency of the present approach to GGS metaheuristic algorithm has been investigated with the help of various test functions. [40][41][42][43][44][45][46][47][48][49][50][51] The tests comprise the Rastrigin (Rn), the Ackley (AKn), the Griewangk (Gn), the Levy (Ln), the Beale (Bn), the Branin (BR), the Goldstein-Price (GP), the Hansen (H), and the Michalewicz (M) functions. The corresponding expressions are given in the Supporting Information, which also reports the global minima and the search ranges for each of the considered functions.…”

Section: Resultsmentioning

confidence: 99%

Gradient gravitational search: An efficient metaheuristic algorithm for global optimization

Dash

Sahu

2015

J. Comput. Chem.

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The adaptation of novel techniques developed in the field of computational chemistry to solve the concerned problems for large and flexible molecules is taking the center stage with regard to efficient algorithm, computational cost and accuracy. In this article, the gradient-based gravitational search (GGS) algorithm, using analytical gradients for a fast minimization to the next local minimum has been reported. Its efficiency as metaheuristic approach has also been compared with Gradient Tabu Search and others like: Gravitational Search, Cuckoo Search, and Back Tracking Search algorithms for global optimization. Moreover, the GGS approach has also been applied to computational chemistry problems for finding the minimal value potential energy of two-dimensional and three-dimensional off-lattice protein models. The simulation results reveal the relative stability and physical accuracy of protein models with efficient computational cost.

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Section: Resultsmentioning

confidence: 99%

Gradient gravitational search: An efficient metaheuristic algorithm for global optimization

Dash

Sahu

2015

J. Comput. Chem.

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“…Therefore, the method of choice in the current work was to perform the optimization in two steps. The initial step used the global optimization method "lowest energy pivot method" (Stanton et al 1997), which randomly distributes a number of points throughout the parameter space and keeps moving the points with the highest energy towards the points with lower energy until the minimum is found. After a sufficient number of steps with this method to find the correct local minimum, the point with the lowest energy was chosen and a Broyden-Fletcher-Goldfarb-Shanno method (Shanno 1970), which is a quasi-Newton local optimizer, was used to quickly find the optimal point.…”

Section: Optimization Proceduresmentioning

confidence: 99%

Wind energy converters and photovoltaics for generation of electricity after natural disasters

Olauson

Goude

Bergkvist

2015

Geografiska Annaler: Series A, Physical Geography

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ABSTRACT. During recovery and reconstruction after a natural disaster, an autonomous power supply might be needed for an extended period of time. In this work, the feasibility of using small-scale wind power and battery storage for power supply is evaluated and compared with systems containing photovoltaics. The investment cost per yearly produced kWh and for an optimized energy system supplying small loads (2 or 20 kW peak) has been calculated for 32 sites, predominantly in Africa and the Middle East. The sites represent foreign activities of the Swedish Civil Contingencies Agency at the end of 2012.Since wind speed measurement series often have a lot of missing data, autoregressive moving average models were trained and used to generate hourly time series of wind speed. This methodology proved robust, even when data availability was very low or when measurements were only taken every third hour. The results of the simulations show that photovoltaic/battery systems outperform wind/battery systems at all evaluated sites. This can be explained by lower investment cost per yearly produced kWh and smoother daily/weekly power output over the year for the photovoltaic system. The proportion of wind power for optimized systems comprising wind, photovoltaics and battery bank is generally very low and the system cost is almost identical to the corresponding photovoltaic/battery systems. In conclusion, at lower latitudes and with little time for a proper wind measurement campaign, photovoltaics should be the primary candidate for replacing or complementing conventional diesel generators.

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“…19 In the pre- vious publication, we tried to keep all parameters of the problem identical for all test functions. In the current publication, we have used four of these parameters ͑number of initial probes, number of probes moved, number of search iterations per standard deviation, , and rate of contraction, R͒ as free parameters.…”

Section: Test Functionsmentioning

confidence: 99%

“…In the original method, 19 the pivots were chosen based on their energies, while in a more efficient version, 20 the pivots were chosen as the nearest neighbor point. The major difference between the methods is the way in which the pivot points are chosen.…”

Section: Introductionmentioning

confidence: 99%

Comparison study of pivot methods for global optimization

Serra

Stanton

Kais

et al. 1997

The Journal of Chemical Physics

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Articles you may be interested inFast optimization of binary clusters using a novel dynamic lattice searching method We compare two implementations of a new algorithm called the pivot method for the location of the global minimum of a multiple minima problem. The pivot method uses a series of randomly placed probes in phase space, moving the worst probes to be near better probes iteratively until the system converges. The original implementation, called the ''lowest energy pivot method,'' chooses the pivot probes with a probability based on the energy of the probe. The second approach, called the ''nearest neighbor pivot method,'' chooses the pivot probes to be the nearest neighbor points in the phase space. We examine the choice of distribution by comparing the efficiency of the methods for Gaussian versus generalized q-distribution, based on the Tsallis entropy in the relocation of the probes. The two implementations of the method are tested with a series of test functions and with several Lennard-Jones clusters of various sizes. It appears that the nearest neighbor pivot method using the generalized q-distribution is superior to previous methods.

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A new approach to global minimization

Cited by 15 publications

References 15 publications

Gradient gravitational search: An efficient metaheuristic algorithm for global optimization

Gradient gravitational search: An efficient metaheuristic algorithm for global optimization

Wind energy converters and photovoltaics for generation of electricity after natural disasters

Comparison study of pivot methods for global optimization

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